Fits Poisson or Gibbs point process model using local likelihood or pseudolikelihood.
locppm(..., sigma = NULL, f = 1/4,
vcalc = c("none", "t", "hessian", "hom", "lik", "full"),
locations=c("split", "fine", "coarse"),
ngrid = NULL, grideps = NULL, verbose = TRUE,
use.fft=FALSE, fft.algorithm="closepairs")An object of class "locppm" representing the fitted model.
Arguments passed to ppm
to fit the homogeneous model.
Standard deviation of Gaussian kernel for local likelihood.
Argument passed to bw.frac to
compute a value for sigma if it is missing or NULL.
Type of variance calculation to be performed. See Details.
Spatial locations for local calculations. See Details.
Dimensions of coarse grid, if used. See Details.
Incompatible with grideps.
Grid spacing of coarse grid, if used. See Details.
Incompatible with ngrid.
Logical. If TRUE, print progress reports.
Logical value indicating whether to perform
computations using the Fast Fourier Transform.
With use.fft = TRUE the code runs much faster
but some quantities are not computed exactly.
See Details.
Developer use only.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au.
This function fits a Poisson or Gibbs point process model to point pattern data by local likelihood or local pseudolikelihood respectively.
This command should be used in the same way as
ppm.
The point pattern data and the specification of the model
are given in the leading arguments ... which are passed
directly to ppm.
In all cases, the local estimates of the coefficients are
computed. However, because the variance calculations are
time-consuming, the default is not to perform them.
This is controlled by the argument vcalc.
vcalc = "none":no variance calculations are performed.
vcalc = "t":the \(t\) statistic for each parameter is computed for the local model.
vcalc = "hessian":the local Hessian matrix is computed, and its negative inverse is used as a surrogate for the local variance.
vcalc = "hom":No local fitting is performed. Calculations are performed only for the homogeneous (template) model. The variance of the local parameter estimates under the homogeneous model is computed.
vcalc = "lik":In addition to the calculations for vcalc="hom" described
above, if use.fft=FALSE
the algorithm also computes the local composite likelihood
ratio test statistic for the test of homogeneity.
If use.fft=TRUE then vcalc="lik" is equivalent to
vcalc="hom".
vcalc = "full":all variance calculations are performed for the local model.
The spatial locations, where the model fits and variance calculations
are performed, are determined by the argument locations.
locations = "fine":The calculations are performed at every quadrature point of the model. This can take a very long time.
locations = "coarse":The calculations are performed at the points of a coarse grid
with dimensions specified by ngrid or grideps.
locations = "split":The fitted coefficients are computed at every quadrature point
of the model, but the variance calculations (if any) are
performed at a coarse grid of locations,
specified by ngrid or grideps.
If neither ngrid nor grideps is specified,
the default is ngrid=10.
If use.fft=FALSE (the default), all desired quantities are
computed exactly, by an iterative algorithm that
fits a separate model at each spatial location. This can be quite
slow.
If use.fft=TRUE, we only compute quantities that can be
obtained using the Fast Fourier Transform, resulting in much faster
calculations (sometimes 3 orders of magnitude faster) when
locations="fine".
Properties of the homogeneous model are
computed accurately. Properties of the locally-fitted model are
approximated by a first order Taylor expansion.
Baddeley, A. (2017) Local composite likelihood
Baddeley, A., Rubak, E. and Turner, R. (2015) Spatial Point Patterns: Methodology and Applications with R. Chapman and Hall/CRC Press.
methods.locppm,
plot.locppm
fit <- locppm(swedishpines, ~1, sigma=9, nd=20)
fit
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